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Runtime Monitors for Markov Decision Processes
[chapter]
2021
Lecture Notes in Computer Science
During runtime, we obtain partial information about the system state in form of observations. The monitor uses this information to estimate the risk of the (unobservable) current system state. ...
AbstractWe investigate the problem of monitoring partially observable systems with nondeterministic and probabilistic dynamics. ...
Markov Decision Processes For a countable set X, let Distr(X) ⊂ (X → [0, 1]) define the set of all distributions over X, i.e., for d ∈ Distr(X) it holds that Σ x∈X d(x) = 1. ...
doi:10.1007/978-3-030-81688-9_26
fatcat:cx26zfi7s5bcdgbmuf2szs43ly
Knowledge Base K Models to Support Trade-Offs for Self-Adaptation using Markov Processes
2019
2019 IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
In this paper, we demonstrate a novel use of Partially Observable Markov Decision Processes (POMDPs) as runtime models to support the decision-making of a Self Adaptive System (SAS) in the context of the ...
Runtime models support decision-making and reasoning for self-adaptation based on both design-time knowledge and information that may emerge at runtime. ...
The authors in [7] , [19] , [18] use a restricted version of POMDPs: Markov Decision Processes (MDPs) or Discrete Time Markov Chains (DTMC), where the knowledge of the state of the system is assumed ...
doi:10.1109/saso.2019.00011
dblp:conf/saso/PaucarB19
fatcat:knysm6t75rdjhgjhz7ro5lxrym
Runtime Software Architecture-Based Reliability Prediction for Self-Adaptive Systems
2022
Symmetry
Based on a Java platform, through non-intrusive monitoring, an RSA behavioral model is obtained followed by runtime reliability analysis model. ...
states at runtime. ...
Acknowledgments: The authors would like to thank the editor and referees for their valuable comments.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/sym14030589
fatcat:lbo7pnijirdxxflgvs3d3lklpe
Towards priority-awareness in autonomous intelligent systems
2021
ACM Symposium on Applied Computing
In this paper, we present a novel use of Multi-Reward Partially Observable Markov Decision Process (MR-POMDP) to support reasoning of separate NFR priorities. ...
Runtime design selection is a trade-off analysis between non-functional requirements (NFRs) that uses optimisation methods, including decision-analysis and utility theory. ...
1, 4, 15, 17] make use of Markov-based approaches such as Markov Decision Process (MDPs), Partially Observable Markov Decision Processes (POMDPs) and Discrete Time Markov Chains (DTMCs) along with probablistic ...
doi:10.1145/3412841.3442007
dblp:conf/sac/SaminPBS21
fatcat:tprh6llx4jaetcsud5aeoj6onm
Mitigating Bottlenecks in Wide Area Data Analytics via Machine Learning
2018
IEEE Transactions on Network Science and Engineering
Lube monitors geodistributed data analytic queries in real-time, detects potential bottlenecks, and mitigates them with a bottleneckaware scheduling policy. ...
In this paper, we present Lube, a system framework that minimizes query response times by detecting and mitigating bottlenecks at runtime. ...
We would like to thank the HotCloud anonymous reviewers for their valuable comments. ...
doi:10.1109/tnse.2018.2816951
fatcat:atngujfnt5cyxhrabf2l5jba2e
SafeDrones: Real-Time Reliability Evaluation of UAVs using Executable Digital Dependable Identities
[article]
2022
arXiv
pre-print
It is a prototype instantiation of the Executable Digital Dependable Identity (EDDI) concept, which aims to create a model-based solution for real-time, data-driven dependability assurance for multi-robot ...
This paper proposes a new reliability modeling approach called SafeDrones to help address this issue by enabling runtime reliability and risk assessment of UAVs. ...
A Semi-Markov Process (SMP) is a special type of Markov process that has the ability to work with nonexponential failure distributions [29] . ...
arXiv:2207.05643v1
fatcat:buarvbzmnvbodckzhhqk63e5ge
PRESTO: Predicting System-level Disruptions through Parametric Model Checking
[article]
2022
arXiv
pre-print
Intended for use in the analysis step of the MAPE-K (Monitor-Analyse-Plan-Execute over a shared Knowledge) feedback control loop of self-adaptive systems, PRESTO comprises two stages. ...
To address this gap, we present a work-in-progress approach for the pre diction of system-level disruptions (PRESTO) through parametric model checking. ...
the MAPE-K monitoring. ...
arXiv:2205.03628v1
fatcat:mq4ndybvazd5xlh7smnsfvuhca
Transition Discovery of Sequential Behaviors in Email Application Usage Using Hidden Markov Models
2013
2013 46th Hawaii International Conference on System Sciences
Herein, we show how the approach applies to monitoring an email application that has been simplified for users having cognitive impairments. ...
This is important for identifying usage transitions, which occur with user learning. ...
Most work in requirements monitoring checks for runtime compliance with design-time properties. ...
doi:10.1109/hicss.2013.574
dblp:conf/hicss/RobinsonAD13
fatcat:5inoq2n46rhmvplicabgd7oshi
State of runtime adaptation in service-oriented systems: what, where, when, how and right
2019
IET Software
However, for adaptation to be effective several other factors need to be considered. ...
This study identifies the key factors that influence runtime adaptation in service-oriented systems (SOSs) and examines how well they are addressed in 29 adaptation approaches intended to support SOSs. ...
Markov decision processes are used to model the problem to be solved as seen in the work of Jureta et al. [64] and Wang et al. [35] . ...
doi:10.1049/iet-sen.2018.5028
fatcat:vkdm64yvybhj5gsptqybj3y6wu
Dynamic decision networks for decision-making in self-adaptive systems: A case study
2013
2013 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)
Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. ...
We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. ...
ACKNOWLEDGMENT We thank Pete Sawyer for his useful feedback. Also thanks to Andres Ramirez for the support on the use of the RDM case study. ...
doi:10.1109/seams.2013.6595498
dblp:conf/icse/BencomoBI13
fatcat:agecq67tszemrhqyhx5pa6q2wa
Model-Based Simulation at Runtime for Self-Adaptive Systems
2016
2016 IEEE International Conference on Autonomic Computing (ICAC)
In this paper, we propose a novel modular approach for decision making in self-adaptive systems that combines distinct models for each relevant quality with runtime simulation of the models. ...
Self-adaptation enables a system to reason about runtime models to adapt itself and realises its goals under uncertainties. Our focus is on providing guarantees for adaption goals. ...
Example -The TAS Monitor comprises Updating components for the different runtime models. ...
doi:10.1109/icac.2016.67
dblp:conf/icac/WeynsI16
fatcat:ypxcoyntkfdzvcnmjmy76ho3fm
A unified stochastic model for energy management in solar-powered embedded systems
2015
2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
We present a unified model based on discrete-time Finite State Markov Chain to capture the dynamicity and variations in both the energy supply from solar irradiance and the energy demand from the application ...
In this paper, we exploit the temporal and spatial characteristics of solar energy and propose a deterministic profile with stochastic process to reflect the fluctuation due to unexpected weather condition ...
The proposed system performance optimization algorithm is based on Markov Decision Process. ...
doi:10.1109/iccad.2015.7372627
dblp:conf/iccad/DangVBLV15
fatcat:jkxtiwsljfcrfibqxvpdq7bzo4
Availability Modeling and Evaluation on High Performance Cluster Computing Systems
2006
Journal of research and practice in information technology
Furthermore, an object oriented Markov model specification to facilitate availability modeling and runtime configuration has been developed. ...
Numerical solutions for Markov models are examined, especially on the uniformization method. ...
better decisions in unleashing HPC power. ...
dblp:journals/acj/SongLN06
fatcat:ritiyyk2bjdbdh2xtwtvrxm5qq
Achieving Adaptation for Adaptive Systems via Runtime Verification: A Model-Driven Approach
[article]
2017
arXiv
pre-print
The adaptation needs to be performed automatically through self-managed reactions and decision-making processes at runtime. ...
Requirements Engineering for SASs primarily aims to model adaptation logic and mechanisms. Requirements models will guide the design decisions and runtime behaviors of sys-tem-to-be. ...
The nondeterminism can be modeled in Markov Decision Processes (MDPs) appropriately. ...
arXiv:1704.00869v1
fatcat:qptllewq25bzthik22mtefpfqa
Review on Requirements Modeling and Analysis for Self-Adaptive Systems: A Ten-Year Perspective
[article]
2017
arXiv
pre-print
Requirements-driven runtime adaptation was the most frequently studied requirements activity. Activities at runtime were conveyed with more details. ...
Context: Over the last decade, software researchers and engineers have developed a vast body of methodologies and technologies in requirements engineering for self-adaptive systems. ...
Kitchenham and her team at Keele University for reviewing our protocol and all the received advice. ...
arXiv:1704.00421v1
fatcat:isttouczxjh5dh7admqaptjzsm
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